Distribution-free control chart Distribution-free control charts are one of the most important tools of statistical process monitoring and control . Implementation techniques of distribution-free control charts do not require any knowledge about the underlying process distribution or its parameters. The main advantage of distribution-free control charts is its in-control robustness, in the sense that, irrespective of the nature of the underlying process distributions , the properties of these control charts remain same when the process is smoothly operating without presence of any assignable cause . Early evidence of research on nonparametric control charts may be found in 1981 when P.K. Bhattacharya and D. Frierson introduced a nonparametric control chart for detecting small disorders . However, major growth of nonparametric control charting schemes has taken place only in the recent years.Popular distribution-free control charts There are distribution-free control charts for both Phase-I analysis and Phase-II monitoring. One of the most notable distribution-free control chart for Phase-I analysis is RS/P chart proposed by G. Capizzi and G. Masaratto. RS/P chart separately monitor location and scale parameters of a univariate process using two separate charts. In 2019 , Chenglong Li , Amitava Mukherjee and Qin Su proposed a single distribution-free control chart for Phase-I analysis using multisample Lepage statistic. Some popular Phase-II distribution-free control charts for univariate continuous processes includes: Sign charts based on the sign statistic - used to monitor location parameter of a process Wilcoxon rank-sum charts based on the Wilcoxon rank-sum test - used to monitor location parameter of a process Control charts based on precedence or exceedance statistic Shewhart-Lepage chart based on the Lepage test - used to monitor both location and scale parameters of a process simultaneously in a single chart Shewhart-Cucconi chart based on the Cucconi test - used to monitor both location and scale parameters of a process simultaneously in a single chart
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